Let’s agree on one thing. Data has become one of the most critical assets a company has.
Now that I’ve got you across the line on the first idea, let’s agree on one more thing. If an asset is critical, then that asset needs to be governed and managed.
Data governance is designed to protect and enhance your organisation’s critical – and non-critical – data assets. To do this effectively, you need to establish a set of data related controls that are expressed through policies, procedures and standards. However, these controls are worthless if they are not being enforced.
To ensure compliance with data controls the data governance team needs to engage with all of the relevant stakeholders. Organisations store most of their data in information systems so a key stakeholder is IT. An important activity for data governance is to engage with IT and ask questions that evaluate information system development from a data perspective.
Let’s agree on one thing. Data has become one of the most critical assets a company has.
Now that I’ve got you across the line on the first idea, let’s agree on one more thing. If an asset is critical, then that asset needs to be governed and managed.
Data governance is designed to protect and enhance your organisation’s critical – and non-critical – data assets. To do this effectively, you need to establish a set of data related controls that are expressed through policies, procedures and standards. However, these controls are worthless if they are not being enforced.
To ensure compliance with data controls the data governance team needs to engage with all of the relevant stakeholders. Organisations store most of their data in information systems so a key stakeholder is IT. An important activity for data governance is to engage with IT and ask questions that evaluate information system development from a data perspective.
Each question should follow a structure. A typical structure is:
- The actual question that needs to be answered
- A rationale for why this question is important
- The impact of failing to adequately address the question
- The set of activities that are required to validate the answer to the question
For example, if a new information system is being developed then data governance professionals should ask:
- Question: Has a data model, that complies with the organisation’s data modelling standard, been created?
- Rationale: A data model will ensure that all data captured by the solution is fully described and understood. The data model is a key input into database design and supports other data related activities such as reporting, user interface design and system to system interfaces.
- Impact: The absence of a data model will risk a database design that is inflexible and poorly understood. Other activities, such as reporting, will be negatively impacted because they will need to re-discover the meaning of the data.
- Activities: Review the data model and assess it against the data modelling standard. Review the data model against the requirements specification. Consult database administrators and other database design stakeholders to ensure the data model meets their needs.
Each question should follow a structure. A typical structure is:
- The actual question that needs to be answered
- A rationale for why this question is important
- The impact of failing to adequately address the question
- The set of activities that are required to validate the answer to the question
For example, if a new information system is being developed then data governance professionals should ask:
- Question: Has a data model, that complies with the organisation’s data modelling standard, been created?
- Rationale: A data model will ensure that all data captured by the solution is fully described and understood. The data model is a key input into database design and supports other data related activities such as reporting, user interface design and system to system interfaces.
- Impact: The absence of a data model will risk a database design that is inflexible and poorly understood. Other activities, such as reporting, will be negatively impacted because they will need to re-discover the meaning of the data.
- Activities: Review the data model and assess it against the data modelling standard. Review the data model against the requirements specification. Consult database administrators and other database design stakeholders to ensure the data model meets their needs.
Other data topics to include in the list of questions include privacy, security, data quality, back ups and data migration.
Engagement should occur at significant milestones in the project life cycle including when the business case is being developed to ensure adequate funding for data related activities.
Any issues that are identified as part of the data engagement process need to be tracked and resolved to ensure the project delivers high quality data assets.
Engagement is a key element in the MIP Data and Analytics Framework. Click here for more details.
Engagement is a key element in the MIP Data and Analytics Framework.
Click here for more details.